Connecting Quality Metrics to Deep Learning Accuracy for Image Fusion Methods-Reference-Cited by-同舟云学术

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Connecting Quality Metrics to Deep Learning Accuracy for Image Fusion Methods

Published:2022-10-19 Issue: Volume: Page:
ISSN:
Container-title:2022 13th International Conference on Information and Communication Technology Convergence (ICTC)
language:
Short-container-title:

Author:

Joo Hosung¹^ORCID,Choi Youngchol²^ORCID,Park Jongwon²^ORCID,Lim Chang Hwy³,Yang Hyun Jong¹^ORCID

Affiliation:

1. Dept. Electrical Engineering (of POSTECH)

2. Korea Research Institute of Ships and Ocean Engineering (KRISO)

3. M1 International Inc.

Funder

Ministry of Oceans and Fisheries

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9952188/9952355/09952709.pdf?arnumber=9952709

Reference26 articles.

1. Principal component analysis-based image fusion routine with application to automotive stamping split detection;zhou;Clemson University,2010

2. Pixel-based and region-based image fusion schemes using ICA bases

3. Multi-directional Laplacian Pyramid Image Fusion Algorithm

4. The Haar wavelet transform: its status and achievements

5. IFCNN: A general image fusion framework based on convolutional neural network

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